RRepoGEO

REPOGEO REPORT · LITE

qdrant/mcp-server-qdrant

Default branch master · commit 06726327 · scanned 5/14/2026, 4:52:01 PM

GitHub: 1,395 stars · 267 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface qdrant/mcp-server-qdrant, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify 'MCP' and LLM integration in the README's opening

    Why:

    CURRENT
    # mcp-server-qdrant: A Qdrant MCP server
    COPY-PASTE FIX
    # mcp-server-qdrant: Qdrant Server for LLM Context & Semantic Memory (Model Context Protocol)
  • mediumtopics#2
    Add more specific LLM integration and context topics

    Why:

    CURRENT
    claude, cursor, llm, mcp, mcp-server, semantic-search, windsurf
    COPY-PASTE FIX
    llm-integration, llm-context, semantic-memory, vector-database-integration, model-context-protocol, qdrant, claude, cursor, windsurf
  • lowreadme#3
    Add a 'Comparison with LLM Frameworks' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison with LLM Frameworks (LangChain, LlamaIndex, etc.)

While frameworks like LangChain and LlamaIndex provide comprehensive tools for building LLM applications, `mcp-server-qdrant` focuses specifically on providing a standardized Model Context Protocol (MCP) server for Qdrant. It acts as a dedicated semantic memory layer, designed to be integrated *by* such frameworks or directly by LLM applications, rather than being a full-fledged orchestration framework itself.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface qdrant/mcp-server-qdrant
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. deepset/Haystack · recommended 1×
  4. Microsoft Semantic Kernel · recommended 1×
  5. OpenAI Functions/Tools · recommended 1×
  • CATEGORY QUERY
    Seeking a framework to connect LLMs with external data for contextual understanding.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack (deepset/Haystack)
    4. Microsoft Semantic Kernel
    5. OpenAI Functions/Tools
    6. LiteLLM

    AI recommended 6 alternatives but never named qdrant/mcp-server-qdrant. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a server for managing LLM semantic memory with vector database integration.
    you: not recommended
    AI recommended (in order):
    1. Weaviate
    2. Pinecone
    3. Qdrant
    4. Milvus
    5. Chroma

    AI recommended 5 alternatives but never named qdrant/mcp-server-qdrant. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of qdrant/mcp-server-qdrant?
    pass
    AI named qdrant/mcp-server-qdrant explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts qdrant/mcp-server-qdrant in production, what risks or prerequisites should they evaluate first?
    pass
    AI named qdrant/mcp-server-qdrant explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo qdrant/mcp-server-qdrant solve, and who is the primary audience?
    pass
    AI named qdrant/mcp-server-qdrant explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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qdrant/mcp-server-qdrant — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite